Hardware independent mapping of multiple sensor configurations for classification of persons

ABSTRACT

Sensors are mounted within a seat structure for measuring seat occupant weight. The sensors can be mounted in any one of various sensor configurations. So that common hardware can be used for each different sensor configuration, a virtual matrix is created and output from the sensors is mapped into the virtual matrix. The virtual matrix includes virtual cell locations that do not have a corresponding sensor output; i.e., there are fewer physical cells (sensors) than virtual cell locations in the virtual matrix. A weight output signal from each sensor is mapped into the corresponding position in the virtual matrix and the remaining virtual cell locations have values assigned to them based on data supplied by the surrounding physical cells. Seat occupant weight is determined based on output from the virtual matrix and the occupant is placed into one of the various occupant classifications. Deployment force of a restraint system is controlled based on the classification of the seat occupant.

RELATED APPLICATIONS

[0001] This application claims priority to provisional applications60/217,581 filed on Jul. 12, 2000, 60/265,533 filed on Jan. 31, 2001,and 60/280,021 filed on Mar. 30, 2001.

BACKGROUND OF THE INVENTION

[0002] 1. Field of the Invention

[0003] This invention relates to a method and apparatus for classifyingvehicle occupants utilizing common hardware for multiple seat sensorconfigurations. Specifically, physical sensors are mapped into a virtualmatrix from which an occupant classification is determined.

[0004] 2. Related Art

[0005] Most vehicles include airbags and seatbelt restraint systems thatwork together to protect the driver and passengers from experiencingserious injuries due to high-speed collisions. It is important tocontrol the deployment force of the airbags based on the size of thedriver or the passenger. When an adult is seated on the vehicle seat,the airbag should be deployed in a normal manner. If there is a smallchild sitting on the vehicle seat, then the airbag should not bedeployed or should be deployed at a significantly lower deploymentforce. One way to control the airbag deployment is to monitor the weightof the seat occupant. The weight information can be used to classifyseat occupants into various groups, e.g., adult, child, infant seat,etc., to ultimately control the deployment force of the airbag.

[0006] There are many different systems for measuring the weight of aseat occupant. One type of system uses a plurality of sensors mountedwithin the seat bottom cushion. Information from the sensors is sent tosystem hardware, which utilizes software to combine the output from thesensors to determine the weight of the seat occupant. Often, thesesensors must be placed symmetrically within the seat cushion in order tobe compatible with the system hardware and software. Sometimes, due tospecific seat design or limited space within the seat cushion,symmetrical placement of the sensors is difficult to achieve.

[0007] Another problem with current seat sensor configurations is thateach different sensor configuration requires different system hardwareand software to account for the variations in sensor placement. Thus, itis difficult to optimize sensor placement because of restrictions withregard to row and column placement of the sensors.

[0008] Thus, it is desirable to have a method and apparatus forclassifying seat occupants that can utilize common hardware and softwarefor different seat sensor configurations. The method and apparatusshould also work with symmetrical as well as non-symmetrical seatconfigurations in addition to overcoming the above referenceddeficiencies with prior art systems.

SUMMARY OF THE INVENTION

[0009] The subject invention includes a method and apparatus forclassifying vehicle occupants utilizing common hardware for multipleseat sensor configurations. Multiple seat sensors are mapped into avirtual matrix from which an occupant classification is determined.

[0010] The seat sensors are preferably mounted within a seat bottomcushion or the seat structure. The sensors can be mounted in asymmetrical or non-symmetrical pattern. The virtual matrix defines anoptimal pattern having an optimal number of seat sensor positions.

[0011] In a disclosed embodiment of this invention, the sensors aremounted in a first configuration having one physical sensor for eachvirtual seat sensor position of the optimal pattern. One occupant weightsignal from each sensor is mapped into one corresponding seat sensorposition in the optimal pattern. Typically, there are more virtual seatsensors positions in the virtual matrix than there are physical seatsensors mounted within the seat. The difference between the number ofvirtual cell locations in the virtual matrix and the number of physicalsensors mounted within the seat bottom define a remaining number ofvirtual cell positions. A value is assigned to each of the remainingvirtual cell positions based on data from the surrounding physicalsensors.

[0012] In a preferred embodiment, electrically erasable programmableread only memory (EEPROM) is used to map the virtual matrix bydetermining values for each of the remaining number of virtual cellpositions. The EEPROM is preferably mounted on a printed circuit boardthat is common to all seat sensor configurations.

[0013] The subject invention provides a method and apparatus forclassifying seat occupants that can be used for symmetrical andnon-symmetrical sensor configurations and utilizes common hardware foreach different seat sensor configurations. These and other features ofthe present invention can be best understood from the followingspecification and drawings, the following of which is a briefdescription.

BRIEF DESCRIPTION OF THE DRAWINGS

[0014]FIG. 1 is a schematic representation of a vehicle seat and airbagsystem incorporating the subject invention.

[0015]FIG. 2 is a schematic view of one seat sensor mountingconfiguration incorporating the subject invention.

[0016]FIG. 3A is a schematic view of an alternate embodiment of a seatsensor mounting configuration incorporating the subject invention.

[0017]FIG. 3B is a schematic view of the sensor configuration of FIG. 3Aincorporating a virtual matrix.

[0018]FIG. 4 is a schematic view of the control system incorporating thesubject invention.

DETAILED DESCRIPTION OF AN EXEMPLARY EMBODIMENT

[0019] A vehicle includes a vehicle seat assembly, shown generally at 12in FIG. 1, and a restraint system including an airbag 14. The seatassembly 12 is preferably a passenger seat and includes a seat back 16and a seat bottom 18. A vehicle occupant 20 exerts a force F against theseat bottom 18. The vehicle occupant 20 can be an adult, child, orinfant in a car seat.

[0020] The airbag system 14 deploys an airbag 24 under certain collisionconditions. The deployment force for the airbag 24, shown as deployed indashed lines in FIG. 1, varies depending upon the type of occupant thatis seated on the seat 12. For and adult, the airbag 24 is deployed in anormal manner shown in FIG. 1. If there is child or an infant in a carseat secured to the vehicle seat 12 then the airbag 24 should not bedeployed or should be deployed at a significantly lower deploymentforce. Thus, it is important to be able to classify seat occupants inorder to control the various restraint systems.

[0021] One way to classify occupants is to monitor and measure theweight force F exerted on the seat bottom 18. Multiple seat sensors 26are mounted within the seat bottom 18 for generating occupant weightsignals 28 representing portions of the occupant weight exerted againsteach respective sensor 26. The signals 28 are transmitted to a centralcontrol unit 30 and the combined output from the sensors 26 is used todetermine seat occupant weight. This process will be discussed ingreater detail below.

[0022] Once seat occupant weight is determined, the occupant isclassified into one of any of the various predetermined occupantclasses, e.g., adult, child, infant, etc. The classification informationcan be used in a variety of ways. For example, the classificationinformation can be used in a vehicle restraint system including anairbag system 14. The classification information can be transmitted toan airbag control. If the classification indicates that an adult is inthe seat 12 then the airbag 24 is deployed in a normal manner. If theclassification indicates that a child or infant is the seat occupantthen the airbag 24 will not be deployed or will be deployed at asignificantly lower deployment force.

[0023] The seat sensors 26 can be mounted within the seat bottom 18 inany of various configurations. The sensors 26 can be mounted in asymmetrical configuration, see FIG. 2, or a non-symmetrical pattern, seeFIG. 4. As shown in FIG. 2, the sensors 26 are preferably mounted intothe seat bottom 18 in a series of rows and columns. The number of rowsand columns can vary, however, FIG. 2 is exemplary of a fully equippedsensor configuration.

[0024]FIG. 3A depicts an alternate sensor mounting configuration. Thisembodiment has one less row, indicated at 30, than the configurationshown in FIG. 2. Reconfiguring the number of rows and/or columns istypically in response to customer requirements for a seat that includesan extra trench to define seat cushion sections. Or, for smaller seats,it may also be necessary to reduce the number of rows and columns.

[0025] In order to utilize common hardware and software with differentseat sensor configurations, a virtual matrix 40 is used to take theplace of the missing row as shown in FIG. 3B. The virtual matrix 40includes virtual cell locations 42 to accommodate the sensors 26 thathave been removed from an ideal pattern. The virtual cells 42 areassigned values based on data from the surrounding physical sensors 26.The central control unit 30 can then utilize an algorithm that is commonto all seat sensor configurations to determine the seat occupant weight.The occupant can then be classified and the airbag system 14 can controlthe airbag deployment force based on this classification.

[0026] As discussed above, the weight signals 28 from the physicalsensors 26 are transmitted to a central control unit 30. As shown inFIG. 4, the central control unit 30 is preferably a printed circuitboard (PCB) 44 that includes a connector 46 with a plurality of portsfor connection to the various sensors 26. The PCB 44 includes a centralprocessor unit (CPU) 48 and electrically erasable programmable read-onlymemory (EEPROM) 50. EEPROM is a type of programmable read-only memorythat can be erased by exposing it to an electrical charge and retainsits contents even when the power is turned off. The CPU 48 and EEPROM 50receive the weight signals 28, generate the virtual matrix 40, and mapthe signals 28 into the matrix 40. The CPU 48 then generates an outputsignal 52 to the airbag assembly 14 to control airbag deployment basedon the seat occupant weight. The operation of PCBs and EEPROMs are wellknown and will not be discussed in further detail. Also, while PCBs andEEPROMs are preferred, other similar components known in the art canalso be used.

[0027] The system operates in the following manner. The sensors 26 aremounted within the seat bottom 18 and generate a plurality of weightsignals 28 in response to a weight force F applied to the seat bottom18. The signals 28 are transmitted to the central control unit 30 wherethey are mapped into virtual cells 42 in the virtual matrix 40. Theoutput from the virtual cells 42 in the matrix 40 is combined and usedto generate an output signal representing the seat occupant weight. Eachseat occupant can then be classified into one of a plurality ofpredetermined occupant weight classes. The classification informationcan then be used to control any of various restraint systems.

[0028] Preferably, the virtual matrix 40 is configured to define anoptimal pattern having an optimal number of virtual cells representingthe optimal or maximum number of seat sensor positions. The virtualmatrix 40 can be generated as a full matrix having a maximum number ofseat sensor positions where each physical sensor 26 is mapped into avirtual cell or the matrix 40 can be generated to represent the“missing” physical sensors 26 that the control unit 30 expects toreceive signals from. In this second embodiment, shown in FIGS. 3A and3B, the weight signals 28 from the physical sensors 28 are combined withthe data generated for the virtual row 30 to determine the seat occupantweight.

[0029] In the preferred embodiment, each sensor signal 28 is mapped intothe virtual matrix 40 as shown in FIG. 4. As discussed above, thephysical seat sensors 26 can be mounted within the seat bottom 18 in anyof various configurations including a symmetrical row/columnconfiguration or a non-symmetrical pattern. For example, in oneconfiguration the sensors 26 can be installed within the seat bottom 18in a pattern that includes one physical sensor 26 for each virtual seatsensor position or cell 42 of the optimal pattern. The control unit 30would then map one occupant weight signal 28 from each physical sensorinto one virtual seat sensor cell 42 in the optimal pattern.

[0030] In the alternative, the physical sensors 26 can be installed inthe seat bottom 18 in an alternate pattern that has fewer physicalsensors 26 than virtual seat sensor cells in the virtual matrix 40. Oneoccupant weight signal 28 from each of the physical sensors 26 is mappedinto a corresponding virtual seat sensor cell 42 in the optimal patternto define a remaining number of virtual sensor positions. A value foreach of the remaining virtual sensor positions is determined based oninformation supplied by surrounding sensors 26.

[0031] Thus, any number of physical sensors 26 can be mounted within aseat in any type of pattern. The weight signals 28 generated by thesensors 26 are then mapped into the virtual matrix 40 and any remainingvirtual cells 42 are assigned values based on information fromsurrounding sensors. Preferably, electrically erasable programmable readonly memory EEPROM is to map the virtual matrix 40 by determining valuesfor each of the remaining number of virtual cells 42 with informationfrom the surrounding cells. Optionally, position tables can be storedwithin the EEPROM to be used in conjunction with occupant weight signals28 from surrounding sensors 26 to determine values for each of theremaining number of virtual cells 42.

[0032] This unique process allows common hardware and software to beused for any seat sensor configuration, which significantly reducessystem cost. This means that the same PCB 44 with the same CPU 48 andEEPROM 50 can be used for each different seat sensor configuration. Thesubject invention also provides a method and apparatus for classifyingseat occupants that can be used for symmetrical and non-symmetricalsensor configurations.

[0033] Although a preferred embodiment of this invention has beendisclosed, it should be understood that a worker of ordinary skill inthe art would recognize many modifications come within the scope of thisinvention. For that reason, the following claims should be studied todetermine the true scope and content of this invention.

I claim:
 1. A method for classifying vehicle occupants by measuring seatoccupant weight comprising the steps of: (a) mounting a plurality ofsensors within a seat structure; (b) generating a plurality of occupantweight signals from the sensors in response to a weight force applied tothe seat structure; (c) mapping the weight signals into a virtualmatrix; and (d) determining seat occupant weight based on the virtualmatrix.
 2. The method according to claim 1 including (f) classifyingeach seat occupant into one of a plurality of predetermined occupantweight classes.
 3. The method according to claim 2 including (g)providing seat occupant weight classification to a restraint control. 4.The method according to claim 1 wherein step (a) further includesmounting the sensors in a non-symmetrical pattern.
 5. The methodaccording to claim 1 wherein step (a) further includes mounting thesensors in a symmetrical pattern.
 6. The method according to claim 1wherein step (c) further includes generating a virtual matrix to definean optimal pattern having an optimal number of seat sensor positions. 7.The method according to claim 6 wherein step (a) includes mounting thesensors into a first predetermined pattern to define a first seat sensorconfiguration wherein the first seat sensor configuration includes onesensor for each seat sensor position of the optimal pattern and step (c)further includes mapping one occupant weight signal from each sensorinto one corresponding seat sensor position in the optimal pattern. 8.The method according to claim 6 wherein step (a) includes mounting afirst number of sensors into a first predetermined pattern to define afirst seat sensor configuration wherein the optimal pattern includesmore seat sensor positions than the first number of sensors; step (c)further includes mapping one occupant weight signal from each of thefirst number of sensors into a corresponding seat sensor position in theoptimal pattern to define a remaining number of virtual sensorpositions, and determining a value for each of the remaining virtualsensor positions based on surrounding sensors from the first number ofsensors.
 9. The method according to claim 8 wherein step (a) includesmounting a second number of sensors into a second predetermined patternto define a second seat sensor configuration that is different from thefirst seat sensor configuration wherein the optimal pattern includesmore seat sensor positions than the second number of sensors; step (c)further includes mapping one occupant weight signal from each of thesecond number of sensors into a corresponding seat sensor position inthe optimal pattern to define a remaining number of virtual sensorpositions, and determining a value for each of the remaining virtualsensor positions based on surrounding sensors from the second number ofsensors.
 10. The method according to claim 1 including providinghardware for receiving the occupant weight signals, storing the virtualmatrix, and mapping the weight signals into the virtual matrix.
 11. Themethod according to claim 10 wherein step (a) includes mounting thesensors into one of multiple different seat sensor configurations andfurther including using common hardware for each different seat sensorconfiguration.
 12. The method according to claim 10 wherein step (a)includes mounting the sensors into one of multiple different seat sensorconfigurations and further including using identical hardware for eachdifferent seat sensor configuration.
 13. The method according to claim 6wherein step (a) includes mounting a predetermined number of sensorswithin the seat structure wherein the predetermined number is less thanthe optimal number of seat sensor positions the difference defining aremaining number of virtual positions and wherein step (c) furtherincludes using a electrically erasable programmable read only memory tomap the virtual matrix by determining values for each of the remainingnumber of virtual positions.
 14. The method according to claim 13including storing position tables within electrically erasableprogrammable read only memory to be used in conjunction with occupantweight signals from surrounding sensors to determine values for each ofthe remaining number of virtual positions.
 15. A method for classifyingvehicle occupants by measuring seat occupant weight comprising the stepsof: (a) mounting a plurality of sensors within a seat structure in aphysical matrix having a first pattern with a first predetermined numberof rows and a first predetermined number of columns; (b) generating aplurality of occupant weight signals from the sensors in response to aweight force applied to the seat structure; (c) generating a virtualmatrix having a second pattern with a second predetermined number ofrows and second predetermined number of columns wherein the secondpredetermined number of rows is greater than or equal to the firstpredetermined number of rows and/or the second predetermined number ofcolumns is greater than or equal to the first predetermined number ofcolumns; (d) mapping the weight signals from the physical matrix intothe virtual matrix by mapping one weight signal from each sensorlocation in the first predetermined number of rows and columns into acorresponding virtual location in the second predetermined number ofrows and columns; and (e) combining data from each of the secondpredetermined number of rows and columns to determine seat occupantweight.
 16. The method of claim 15 wherein the difference between thesecond predetermined number of rows and columns and the firstpredetermined number of rows and columns defines virtual sensorlocations and step (d) further includes determining a value for eachvirtual sensor location by using data from the surrounding sensors inthe first predetermined number of rows and columns.
 17. The method ofclaim 16 wherein step (a) includes having a plurality of different firstpatterns to define a plurality of sensor configurations and includingthe step of using common hardware and software for every sensorconfiguration.
 18. The method of claim 17 including using electricallyerasable programmable read only memory for the mapping.
 19. A system fordetermining seat occupant weight comprising: a plurality of sensorsmounted within a seat structure for generating a plurality of occupantweight signals in response to a weight force applied to said seatstructure; and a control unit electrically connected to said sensors forreceiving said signals and mapping said signals into a virtual matrix togenerate an output signal representing seat occupant weight.
 20. Asystem according to claim 19 wherein said control unit generates saidvirtual matrix to define an optimal pattern having an optimal number ofseat sensor positions and wherein said plurality of sensors are mountedwithin said seat structure to establish a first sensor configurationhaving a first predetermined number of sensors that is less than theoptimal number of sensors to define a number of remaining virtual sensorpositions, said control unit mapping one occupant weight signal into acorresponding seat sensor position in said virtual matrix and assigninga value to each of said remaining virtual sensor positions by utilizingweight signals from surrounding sensors.
 21. A system according to claim19 wherein said sensors are mounted within said seat structure in one ofa plurality of seat sensor configurations and wherein said control unitincludes hardware that is common to each of said seat sensorconfigurations.
 22. A system according to claim 19 wherein said controlunit includes electrically erasable programmable read only memory.
 23. Asystem according to claim 19 wherein said control unit includes aprinted circuit board having a plurality of connectors for attachment tosaid sensors and a central processing unit for generating said virtualmatrix and mapping said weight signals into said virtual matrix.
 24. Asystem according to claim 19 including a restraint control wherein saidoutput signal is classified into one of a plurality of predeterminedoccupant weight classes and transmitted to said restraint control.